This page has only limited features, please log in for full access.

Dr. Amir M. Fathollahi-Fard
École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada

Basic Info

Basic Info is private.

Research Keywords & Expertise

0 Heuristics
0 Metaheuristics
0 Optimization Algorithms
0 Supply Chain Management
0 Healthcare Systems

Fingerprints

Metaheuristics
Heuristics
Supply Chain Management

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 28 August 2021 in Journal of Environmental Management
Reads 0
Downloads 0

Nowadays, releasing the Emerging Pollutants (EPs) in the nature is one of the main reasons for many health and environmental disasters. Amoxicillin as an antibiotic is one of the EPs and categorized as the Endocrine Disrupting Compounds (EDCs) in hazardous materials. Accumulation of amoxicillin in the soil bulk increases the cancer risk, drug resistances and other epidemiological diseases. Hence, the soil bioremediation of antibiotics can be a solution for this problem which is more environmental-friendly system. This study technically creates a bio-engine setup in soil bulk for remediation of amoxicillin based on Aspergillus Flavus (AF) activities and Removal Percentage (RP) of amoxicillin with Aflatoxin B1 Generation (AG) controls. The main novelty is to propose a hybrid computational intelligence approach to do optimization for mechanical and biological aspects and to predict the behavior of bio-engine's effective mechanical and biological features in an intelligent way. The optimization model is formulated by the Central Composite Design (CCD) which is set by the Response Surface Methodology (RSM). The prediction model is formulated by the Random Forest (RF), Adaptive Neuro Fuzzy Inference System (ANFIS) and Random Tree (RT) algorithms. According to the experimental practices from real soil samples in different times and places, concentration of amoxicillin and Aflatoxin B1 are set equal to 25 mg/L (ppm) and 15 μg/L (ppb). Likewise, the outcomes of experiments in CCD-RSM computations are evaluated by curve fitting comparisons between linear, 2FI, quadratic and cubic polynomial equations with considering to regression coefficient and predicted regression coefficient values, ANOVA and optimization by sequential differentiation. Based on the results of CCD-RSM, the RP performance in the optimum conditions is measured around 86% and in 25 days after runtime, the RP and AG are balanced in the safe mode. The proposed hybrid model achieves the 0.99 accuracy. The applicability of the research is done using real field evaluations from drug industrial park in Mashhad city in Iran. Finally, a broad analysis is done and managerial insights are concluded. The main findings of the present research are: (I) with application of bioremediation from fungus activities, amoxicillin amounts can be control in soil resources with minimum AG, (II) ANFIS model has the best accuracy for smart monitoring of amoxicillin bioremediation in soil environments and (III) based on the statistical assessments Aeration Intensity and AF/Biological Waste ratio are most effective on the amoxicillin removal percentage.

ACS Style

Maryam Mohammadi; Mohammad Gheibi; Amir M. Fathollahi-Fard; Mohammad Eftekhari; Zahra Kian; Guangdong Tian. A hybrid computational intelligence approach for bioremediation of amoxicillin based on fungus activities from soil resources and aflatoxin B1 controls. Journal of Environmental Management 2021, 299, 113594 .

AMA Style

Maryam Mohammadi, Mohammad Gheibi, Amir M. Fathollahi-Fard, Mohammad Eftekhari, Zahra Kian, Guangdong Tian. A hybrid computational intelligence approach for bioremediation of amoxicillin based on fungus activities from soil resources and aflatoxin B1 controls. Journal of Environmental Management. 2021; 299 ():113594.

Chicago/Turabian Style

Maryam Mohammadi; Mohammad Gheibi; Amir M. Fathollahi-Fard; Mohammad Eftekhari; Zahra Kian; Guangdong Tian. 2021. "A hybrid computational intelligence approach for bioremediation of amoxicillin based on fungus activities from soil resources and aflatoxin B1 controls." Journal of Environmental Management 299, no. : 113594.

Original paper
Published: 09 August 2021 in International Journal of Environmental Science and Technology
Reads 0
Downloads 0

Application of construction and demolition (C&D) wastes were considered as sustainable development goals (SDGs) for maintaining raw materials. Also, lightweight concretes such as aerated autoclaved concrete (AAC) were used for partitioning spaces in the building industry. Moreover, the waste products of the mentioned materials were increased due to the rise of old construction demolitions. This study contributes a calcinated aerated autoclaved concrete (CAAC) which is efficient, powerful, highly rapid, non-expensive and novel adsorbent for the removal of cationic dyes including malachite green (MG), methyl violet (MV) and methylene blue (MB) form water samples. The impacts of different variables for the proposed system including initial pH value, stirring rate, dye concentration and contact time are explored to optimize the selected analyses. Most notably, this study analyzes the experimental isotherm data by using two-parameter isotherms such as Dubinin–Radushkevich, Temkin, Langmuir and Freundlich equations and three-parameter isotherms including Koble–Corrigan, Toth, Redlich–Peterson and Sips models. The maximum adsorption capacities for MG, MB and MV are 370.4, 256.4 and 277.8 mg g−1, respectively. In addition, five kinetic models, Elovich, intraparticle diffusion, main equations of pseudo-first- and second-order, and Boyd mathematical models are employed to follow the kinetic parameters and adsorption process of each dye. The Boyd equations indicate that with regard to all three dyes and at all concentrations, the film diffusion is dominant over intraparticle diffusions. Almost none of the geometric plots of adsorption and desorption curves intersected, indicating the adsorption process is optimally performed.

ACS Style

M. Gheibi; M. Eftekhari; M. G. Tabrizi; A. M. Fathollahi-Fard; G. Tian. Mechanistic evaluation of cationic dyes adsorption onto low-cost calcinated aerated autoclaved concrete wastes. International Journal of Environmental Science and Technology 2021, 1 -16.

AMA Style

M. Gheibi, M. Eftekhari, M. G. Tabrizi, A. M. Fathollahi-Fard, G. Tian. Mechanistic evaluation of cationic dyes adsorption onto low-cost calcinated aerated autoclaved concrete wastes. International Journal of Environmental Science and Technology. 2021; ():1-16.

Chicago/Turabian Style

M. Gheibi; M. Eftekhari; M. G. Tabrizi; A. M. Fathollahi-Fard; G. Tian. 2021. "Mechanistic evaluation of cationic dyes adsorption onto low-cost calcinated aerated autoclaved concrete wastes." International Journal of Environmental Science and Technology , no. : 1-16.

Preprint content
Published: 02 June 2021
Reads 0
Downloads 0

One of the significant challenges in urbanization is the air pollution. This highlights the need of the green city concept with reconsideration of houses, factories and traffics in a green viewpoint. The literature review confirms that this reconsideration for green space, has a positive effect on the air quality of large cities and to remove the air pollution. The purpose of this study is to evaluate the annual vegetation changes in the green space of Mashhad, Iran as a very populated city in the middle east to study the air pollution. To investigate the relationship between the air pollution and vegetation, the Landsat 8 satellite images for summers of 2013-2019 were used to extract changes in vegetation by calculating the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Optimized Soil Adjusted Vegetation Index (OSAVI). The main contribution in comparison with the relevant studies is to study the relationship between clean, healthy and unhealthy days with the green space area for the first time in Mashhad, Iran. The results show that the implementation of green city concept in Mashhad, Iran has been increased by 64%, 81% and 53% by NDVI, EVI and OSAVI, respectively during the study period. The vegetation area of this city is positively correlated to clean and healthy days and has a negative correlation to unhealthy days, in which the greatest values for NDVI, EVI and OSAVI are 0.33, 0.52 and -0.53, respectively.

ACS Style

Amir Nejatian; Masoud Makian; Mohammad Gheibi; Amir Mohammad Fathollahi-Fard. A Novel Viewpoint to the Green City Concept Based on Vegetation Area Changes and Contributions to Healthy Days: A Case Study of Mashhad, Iran. 2021, 1 .

AMA Style

Amir Nejatian, Masoud Makian, Mohammad Gheibi, Amir Mohammad Fathollahi-Fard. A Novel Viewpoint to the Green City Concept Based on Vegetation Area Changes and Contributions to Healthy Days: A Case Study of Mashhad, Iran. . 2021; ():1.

Chicago/Turabian Style

Amir Nejatian; Masoud Makian; Mohammad Gheibi; Amir Mohammad Fathollahi-Fard. 2021. "A Novel Viewpoint to the Green City Concept Based on Vegetation Area Changes and Contributions to Healthy Days: A Case Study of Mashhad, Iran." , no. : 1.

Journal article
Published: 12 April 2021 in Symmetry
Reads 0
Downloads 0

Product disassembly and recycling are important issues in green design. Disassembly sequence planning (DSP) is an important problem in the product disassembly process. The core idea is to generate the best or approximately optimal disassembly sequence to reduce disassembly costs and time. According to the characteristics of the DSP problem, a new algorithm to solve the DSP problem is proposed. Firstly, a disassembly hybrid graph is introduced, and a disassembly constraint matrix is established. Secondly, the disassembling time, replacement frequency of disassembly tool and replacement frequency of disassembly direction are taken as evaluation criteria to establish the product fitness function. Then, an improved social engineering optimizer (SEO) method is proposed. In order to enable the algorithm to solve the problem of disassembly sequence planning, a swap operator and swap sequence are introduced, and steps of the social engineering optimizer are redefined. Finally, taking a worm reducer as an example, the proposed algorithm is used to generate the disassembly sequence, and the influence of the parameters on the optimization results is analyzed. Compared with several heuristic intelligent optimization methods, the effectiveness of the proposed method is verified.

ACS Style

Cheng Zhang; Amir Fathollahi-Fard; Jianyong Li; Guangdong Tian; Tongzhu Zhang. Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer. Symmetry 2021, 13, 663 .

AMA Style

Cheng Zhang, Amir Fathollahi-Fard, Jianyong Li, Guangdong Tian, Tongzhu Zhang. Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer. Symmetry. 2021; 13 (4):663.

Chicago/Turabian Style

Cheng Zhang; Amir Fathollahi-Fard; Jianyong Li; Guangdong Tian; Tongzhu Zhang. 2021. "Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer." Symmetry 13, no. 4: 663.

Journal article
Published: 01 April 2021 in Advanced Engineering Informatics
Reads 0
Downloads 0

The maritime transportation flows and container demand have been increasing over time, although the COVID-19 pandemic may slow down this trend for some time. One of the common strategies adopted by shipping lines to efficiently serve the existing customers is the deployment of large ships. The current practice in the liner shipping industry is to deploy a combination of ships of different types with different carrying capacities (i.e., heterogeneous fleet), especially at the routes with a significant demand. However, heterogeneous fleets of ships have been investigated by a very few studies addressing the tactical liner shipping decisions (i.e., determination of service frequency, ship fleet deployment, optimization of ship sailing speed, and design of ship schedules). Moreover, limited research efforts have been carried out to simultaneously capture all the major tactical liner shipping decisions using a single solution methodology. Therefore, this study proposes an integrated optimization model that addresses all the major tactical liner shipping decisions and allows the deployment of a heterogeneous ship fleet at each route, considering emissions generated throughout liner shipping operations. The model’s objective maximizes the total turnaround profit generated from liner shipping operations. A decomposition-based heuristic algorithm is presented in this study to solve the model proposed and efficiently tackle large-size problem instances. Numerical experiments, carried out for a number of real-world liner shipping routes, demonstrate the effectiveness of the proposed methodology. A set of managerial insights, obtained from the proposed methodology, are also provided.

ACS Style

Junayed Pasha; Maxim A. Dulebenets; Amir M. Fathollahi-Fard; Guangdong Tian; Yui-Yip Lau; Prashant Singh; Benbu Liang. An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations. Advanced Engineering Informatics 2021, 48, 101299 .

AMA Style

Junayed Pasha, Maxim A. Dulebenets, Amir M. Fathollahi-Fard, Guangdong Tian, Yui-Yip Lau, Prashant Singh, Benbu Liang. An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations. Advanced Engineering Informatics. 2021; 48 ():101299.

Chicago/Turabian Style

Junayed Pasha; Maxim A. Dulebenets; Amir M. Fathollahi-Fard; Guangdong Tian; Yui-Yip Lau; Prashant Singh; Benbu Liang. 2021. "An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations." Advanced Engineering Informatics 48, no. : 101299.

Journal article
Published: 16 March 2021 in Computers & Industrial Engineering
Reads 0
Downloads 0

An efficient product distribution is critical for proper supply chain operations. Many supply chains handle perishable products that decay over time. Due to mismanagement of supply chain operations, a significant portion of perishable products is wasted, resulting in substantial monetary losses. Cross-docking terminals (CDTs) have been widely used in cold supply chains for the product distribution but have not received adequate attention in the scientific literature. To improve the efficiency of perishable product distribution, this study introduces for the first time a novel mixed-integer mathematical formulation for the truck scheduling optimization at a cold-chain CDT. The model explicitly captures the decay of perishable products throughout the service of arriving trucks and accounts for the presence of temperature-controlled storage areas that are specifically designated for perishable products. The objective minimizes the total cost incurred during the truck service. Considering the complexity of the proposed model, a customized Evolutionary Algorithm is developed to solve it. The computational performance of the developed algorithm is assessed throughout the numerical experiments based on a detailed comparative analysis against the other metaheuristics. The developed Evolutionary Algorithm is found to be the most promising metaheuristic, considering both solution quality and CPU time perspectives. Furthermore, the proposed algorithm demonstrates an acceptable stability of the solution quality at termination. A set of additional sensitivity analyses are performed in order to draw some significant managerial implications, which would be of potential interest to the supply chain stakeholders that are involved in the distribution of perishable products in cold supply chains.

ACS Style

Oluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Yui-Yip Lau; Amir M. Fathollahi-Fard; Arash Mazaheri. Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations. Computers & Industrial Engineering 2021, 156, 107240 .

AMA Style

Oluwatosin Theophilus, Maxim A. Dulebenets, Junayed Pasha, Yui-Yip Lau, Amir M. Fathollahi-Fard, Arash Mazaheri. Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations. Computers & Industrial Engineering. 2021; 156 ():107240.

Chicago/Turabian Style

Oluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Yui-Yip Lau; Amir M. Fathollahi-Fard; Arash Mazaheri. 2021. "Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations." Computers & Industrial Engineering 156, no. : 107240.

Review
Published: 27 February 2021 in Environmental Science and Pollution Research
Reads 0
Downloads 0

Blockchain is a distributed ledger technology that has attracted both practitioners and academics attention in recent years. Several conceptual and few empirical studies have been published focusing on addressing current issues and recommending the future research directions of supply chain management. To identify how blockchain can contribute to supply chain management, this paper conducts a systematic review through bibliometric and network analysis. We determined the key authors, significant studies, and the collaboration patterns that were not considered by the previous publications on this angel of supply chain management. Using citation and co-citation analysis, key supply chain areas that blockchain could contribute are pinpointed as supply chain management, finance, logistics, and security. Furthermore, it revealed that Internet of Things (IoT) and smart contracts are the leading emerging technologies in this field. The results of highly cited and co-cited articles demonstrate that blockchain could enhance transparency, traceability, efficiency, and information security in supply chain management. The analysis also revealed that empirical research is scarce in this field. Therefore, implementing blockchain in the real-world supply chain is a considerable future research opportunity.

ACS Style

Javid Moosavi; Leila M. Naeni; Amir M. Fathollahi-Fard; Ugo Fiore. Blockchain in supply chain management: a review, bibliometric, and network analysis. Environmental Science and Pollution Research 2021, 1 -15.

AMA Style

Javid Moosavi, Leila M. Naeni, Amir M. Fathollahi-Fard, Ugo Fiore. Blockchain in supply chain management: a review, bibliometric, and network analysis. Environmental Science and Pollution Research. 2021; ():1-15.

Chicago/Turabian Style

Javid Moosavi; Leila M. Naeni; Amir M. Fathollahi-Fard; Ugo Fiore. 2021. "Blockchain in supply chain management: a review, bibliometric, and network analysis." Environmental Science and Pollution Research , no. : 1-15.

Journal article
Published: 10 February 2021 in Expert Systems with Applications
Reads 0
Downloads 0

The purpose of this paper is to develop a framework to identify, analyze, and to assess supply chain disruption factors and drivers. Based on an empirical analysis, four disruption factor categories including natural, human-made, system accidents, and financials with a total of sixteen disruption drivers are identified and examined in a real-world industrial setting. This research utilizes an integrated approach comprising both the Delphi method and the fuzzy analytic hierarchy process (FAHP). To test this integrated method, one of the well-known examples in industrial contexts of developing countries, the ready-made garment industry in Bangladesh is considered. To evaluate this industrial example, a sensitivity analysis is conducted to ensure the robustness and viability of the framework in practical settings. This study not only expands the literature scope of supply chain disruption risk assessment but through its application in any context or industry will reduce the impact of such disruptions and enhance the overall supply chain resilience. Consequently, these enhanced capabilities arm managers the ability to formulate relevant mitigation strategies that are robust and computationally efficient. These strategies will allow managers to take calculated decisions proactively. Finally, the results reveal that political and regulatory instability, cyclones, labor strikes, flooding, heavy rain, and factory fires are the top six disruption drivers causing disruptions to the ready-made garment industry in Bangladesh.

ACS Style

Syed Mithun Ali; Sanjoy Kumar Paul; Priyabrata Chowdhury; Renu Agarwal; Amir Mohammad Fathollahi-Fard; Charbel Jose Chiappetta Jabbour; Sunil Luthra. Modelling of supply chain disruption analytics using an integrated approach: An emerging economy example. Expert Systems with Applications 2021, 173, 114690 .

AMA Style

Syed Mithun Ali, Sanjoy Kumar Paul, Priyabrata Chowdhury, Renu Agarwal, Amir Mohammad Fathollahi-Fard, Charbel Jose Chiappetta Jabbour, Sunil Luthra. Modelling of supply chain disruption analytics using an integrated approach: An emerging economy example. Expert Systems with Applications. 2021; 173 ():114690.

Chicago/Turabian Style

Syed Mithun Ali; Sanjoy Kumar Paul; Priyabrata Chowdhury; Renu Agarwal; Amir Mohammad Fathollahi-Fard; Charbel Jose Chiappetta Jabbour; Sunil Luthra. 2021. "Modelling of supply chain disruption analytics using an integrated approach: An emerging economy example." Expert Systems with Applications 173, no. : 114690.

Research article
Published: 05 February 2021 in International Journal of Systems Science: Operations & Logistics
Reads 0
Downloads 0

This paper proposes a multi-objective robust-stochastic humanitarian logistics model to assist disaster management officials in making optimal pre- and post-disaster decisions. This model identifies the location of temporary facilities, determines the amount of commodity to be pre-positioned, and provides a detailed schedule for the distribution of commodities and the dispatch of vehicles. Uncertainties in demand, node reachability by a particular mode of transportation, and condition of pre-positioned supplies after a disaster are considered. Another supposition of this paper is the equity in the distribution of commodities. This paper contributes to the existing literature by adding vehicle flow and multi-periodicity into a robust-stochastic optimisation model. A real-life case study of a flood in Bangladesh shows the applicability of our model. Finally, the findings show that the proposed model can aid decision-makers in allocating resources optimally.

ACS Style

Zuhayer Mahtab; Abdullahil Azeem; Syed Mithun Ali; Sanjoy Kumar Paul; Amir Mohammad Fathollahi-Fard. Multi-objective robust-stochastic optimisation of relief goods distribution under uncertainty: a real-life case study. International Journal of Systems Science: Operations & Logistics 2021, 1 -22.

AMA Style

Zuhayer Mahtab, Abdullahil Azeem, Syed Mithun Ali, Sanjoy Kumar Paul, Amir Mohammad Fathollahi-Fard. Multi-objective robust-stochastic optimisation of relief goods distribution under uncertainty: a real-life case study. International Journal of Systems Science: Operations & Logistics. 2021; ():1-22.

Chicago/Turabian Style

Zuhayer Mahtab; Abdullahil Azeem; Syed Mithun Ali; Sanjoy Kumar Paul; Amir Mohammad Fathollahi-Fard. 2021. "Multi-objective robust-stochastic optimisation of relief goods distribution under uncertainty: a real-life case study." International Journal of Systems Science: Operations & Logistics , no. : 1-22.

Journal article
Published: 04 August 2020 in Renewable and Sustainable Energy Reviews
Reads 0
Downloads 0

With the increasing production and marketing of new energy vehicles (NEVs) in China, a large number of electric vehicles (EVs) batteries produced by the scrapped NEVs pose a great threat to environmental regulations and social security. Due to the influence of battery type, model, material, battery status, vehicle information and other factors, the scrapped new energy vehicle battery failed to achieve efficient and convenient recycling. Considering the requirements of some recently published government documents and the characteristics of electric vehicle battery, an integrated vehicle identification number (VIN) code is proposed. Based on the analysis of the current national standards GB 16735–2019 road vehicle-VIN identification number and GB/T 34,014–2017 code rules for vehicle power battery, the standard of combining battery code and tracking code is proposed. Finally, the possible coordination code is applied to a case study. The research results of this paper have been implanted into China's national standards.

ACS Style

Haijun Yu; Hongliang Dai; Guangdong Tian; Benben Wu; Yinghao Xie; Ying Zhu; Tongzhu Zhang; Amir Mohammad Fathollahi-Fard; Qi He; Hong Tang. Key technology and application analysis of quick coding for recovery of retired energy vehicle battery. Renewable and Sustainable Energy Reviews 2020, 135, 110129 .

AMA Style

Haijun Yu, Hongliang Dai, Guangdong Tian, Benben Wu, Yinghao Xie, Ying Zhu, Tongzhu Zhang, Amir Mohammad Fathollahi-Fard, Qi He, Hong Tang. Key technology and application analysis of quick coding for recovery of retired energy vehicle battery. Renewable and Sustainable Energy Reviews. 2020; 135 ():110129.

Chicago/Turabian Style

Haijun Yu; Hongliang Dai; Guangdong Tian; Benben Wu; Yinghao Xie; Ying Zhu; Tongzhu Zhang; Amir Mohammad Fathollahi-Fard; Qi He; Hong Tang. 2020. "Key technology and application analysis of quick coding for recovery of retired energy vehicle battery." Renewable and Sustainable Energy Reviews 135, no. : 110129.

Research article
Published: 03 August 2020 in Environmental Science and Pollution Research
Reads 0
Downloads 0

In this paper, folic acid–coated graphene oxide nanocomposite (FA-GO) is used as an adsorbent for the treatment of heavy metals including cadmium (Cd2+) and copper (Cu2+) ions. As such, graphene oxide (GO) is modified by folic acid (FA) to synthesize FA-GO nanocomposite and characterized by the atomic force microscopy (AFM), Fourier transform-infrared (FT-IR) spectrophotometry, scanning electron microscopy (SEM), and C/H/N elemental analyses. Also, computational intelligence tests are used to study the mechanism of the interaction of FA molecules with GO. Based on the results, FA molecules formed a strong π-π stacking, chemical, and hydrogen bond interactions with functional groups of GO. Main parameters including pH of the sample solution, amounts of adsorbent, and contact time are studied and optimized by the Response Surface Methodology Based on Central Composite Design (RSM-CCD). In this study, the equilibrium of adsorption is appraised by two (Langmuir and Freundlich and Temkin and D-R models) and three parameter (Sips, Toth, and Khan models) isotherms. Based on the two parameter evaluations, Langmuir and Freundlich models have high accuracy according to the R2 coefficient (more than 0.9) in experimental curve fittings of each pollutant adsorption. But, multilayer adsorption of each contaminant onto the FA-GO adsorbent (Freundlich equation) is demonstrated by three parameter isotherm analysis. Also, isotherm calculations express maximum computational adsorption capacities of 103.1 and 116.3 mg g−1 for Cd2+ and Cu2+ ions, correspondingly. Kinetic models are scrutinized and the outcomes depict the adsorption of both Cd2+ and Cu2+ followed by the pseudo-second-order equation. Meanwhile, the results of the geometric model illustrate that the variation of adsorption and desorption rates do not have any interfering during the adsorption process. Finally, thermodynamic studies show that the adsorption of Cu2+ and Cd2+ onto the FA-GO nanocomposite is an endothermic and spontaneous process.

ACS Style

Mohammad Eftekhari; Mehran Akrami; Mohammad Gheibi; Hossein Azizi-Toupkanloo; Amir Mohammad Fathollahi-Fard; Guangdong Tian. Cadmium and copper heavy metal treatment from water resources by high-performance folic acid-graphene oxide nanocomposite adsorbent and evaluation of adsorptive mechanism using computational intelligence, isotherm, kinetic, and thermodynamic analyses. Environmental Science and Pollution Research 2020, 27, 43999 -44021.

AMA Style

Mohammad Eftekhari, Mehran Akrami, Mohammad Gheibi, Hossein Azizi-Toupkanloo, Amir Mohammad Fathollahi-Fard, Guangdong Tian. Cadmium and copper heavy metal treatment from water resources by high-performance folic acid-graphene oxide nanocomposite adsorbent and evaluation of adsorptive mechanism using computational intelligence, isotherm, kinetic, and thermodynamic analyses. Environmental Science and Pollution Research. 2020; 27 (35):43999-44021.

Chicago/Turabian Style

Mohammad Eftekhari; Mehran Akrami; Mohammad Gheibi; Hossein Azizi-Toupkanloo; Amir Mohammad Fathollahi-Fard; Guangdong Tian. 2020. "Cadmium and copper heavy metal treatment from water resources by high-performance folic acid-graphene oxide nanocomposite adsorbent and evaluation of adsorptive mechanism using computational intelligence, isotherm, kinetic, and thermodynamic analyses." Environmental Science and Pollution Research 27, no. 35: 43999-44021.

Journal article
Published: 08 June 2020 in Scientia Iranica
Reads 0
Downloads 0

A bi-objective non-linear optimization model with the goal of maximizing the profit of inventory and minimizing the carbon emissions of transportation, simultaneously, is developed. Another contribution of this work is to propose three capable metaheuristics to solve it optimality in large-scale samples. In this regard, the Non-dominated Sorting Genetic Algorithm (NSGA-II) as a well-known method as well as Multi-Objective of Keshtel Algorithm (MOKA) and Multi-Objective of Red Deer Algorithm (MORDA) are firstly applied in this research area. The results of metaheuristics are checked by the ε-constraint method in a set of small-scale samples as compared with the results of literature. Finally, the outputs confirm that the allowed shortage situation along with the lack of cost reduction shows a greater amount of shipping and orders. As such, the performance of MORDA is approved in comparison with MOKA and NSGA-II through different criteria.

ACS Style

Mohammad Mahdi Karampour; Mostafa Hajiaghaei-Keshteli; Amir Mohammad Fathollahi-Fard; Guangdong Tian. Metaheuristics for a bi-objective green vendor managed inventory problem in a two-echelon supply chain network. Scientia Iranica 2020, 1 .

AMA Style

Mohammad Mahdi Karampour, Mostafa Hajiaghaei-Keshteli, Amir Mohammad Fathollahi-Fard, Guangdong Tian. Metaheuristics for a bi-objective green vendor managed inventory problem in a two-echelon supply chain network. Scientia Iranica. 2020; ():1.

Chicago/Turabian Style

Mohammad Mahdi Karampour; Mostafa Hajiaghaei-Keshteli; Amir Mohammad Fathollahi-Fard; Guangdong Tian. 2020. "Metaheuristics for a bi-objective green vendor managed inventory problem in a two-echelon supply chain network." Scientia Iranica , no. : 1.

Articles
Published: 29 May 2020 in International Journal of Systems Science: Operations & Logistics
Reads 0
Downloads 0

There is a great deal of interest in addressing humanitarian logistics due to the need for emergency services in the case of disaster. Controlling both operational and disruption uncertainties in the emergency management is one of challenging topics lately to propose a robust plan for humanitarian logistics. Designing a robust and resilient humanitarian relief chain networks under both operational and disruptive risks can ensure the delivery of the essential supplies to beneficiaries. In this paper, a humanitarian logistic network design with multiple central warehouses and local distribution centres in an integrated manner is addressed by a novel scenario-based possibilistic-stochastic programming approach. The main real-life application of the proposed methodology is to consider the transportation network's routes after an earthquake to provide a plan against uncertainty in whole levels of supply chain along with its availability. To this end, a real case study of Mazandaran province in the north of Iran is provided to validate our methodology as well as a comprehensive discussion and managerial insights are concluded from the results.

ACS Style

Ali Mehdi Nezhadroshan; Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli. A scenario-based possibilistic-stochastic programming approach to address resilient humanitarian logistics considering travel time and resilience levels of facilities. International Journal of Systems Science: Operations & Logistics 2020, 1 -27.

AMA Style

Ali Mehdi Nezhadroshan, Amir Mohammad Fathollahi-Fard, Mostafa Hajiaghaei-Keshteli. A scenario-based possibilistic-stochastic programming approach to address resilient humanitarian logistics considering travel time and resilience levels of facilities. International Journal of Systems Science: Operations & Logistics. 2020; ():1-27.

Chicago/Turabian Style

Ali Mehdi Nezhadroshan; Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli. 2020. "A scenario-based possibilistic-stochastic programming approach to address resilient humanitarian logistics considering travel time and resilience levels of facilities." International Journal of Systems Science: Operations & Logistics , no. : 1-27.

Journal article
Published: 08 May 2020 in Applied Soft Computing
Reads 0
Downloads 0

Home care services are an alternative answer to hospitalization, and play an important role in reducing the healthcare costs for governments and healthcare practitioners. To find a valid plan for these services, an optimization problem called the home healthcare routing and scheduling problem is motivated to perform the logistics of the home care services. Although most studies mainly focus on minimizing the total cost of logistics activities, no study, as far as we know, has treated the patients’ satisfaction as an objective function under uncertainty. To make this problem more practical, this study proposes a bi-objective optimization methodology to model a multi-period and multi-depot home healthcare routing and scheduling problem in a fuzzy environment. With regards to a group of uncertain parameters such as the time of travel and services as well as patients’ satisfaction, a fuzzy approach named as the Jimenez’s method, is also utilized. To address the proposed home healthcare problem, new and well-established metaheuristics are obtained. Although the social engineering optimizer (SEO) has been applied to several optimization problems, it has not yet been applied in the healthcare routing and scheduling area. Another innovation is to develop a new modified multi-objective version of SEO by using an adaptive memory strategy, so-called AMSEO. Finally, a comprehensive discussion is provided by comparing the algorithms based on multi-objective metrics and sensitivity analyses. The practicality and efficiency of the AMSEO in this context lends weight to the development and application of the approach more broadly.

ACS Style

Amir Mohammad Fathollahi-Fard; Abbas Ahmadi; Fariba Goodarzian; Naoufel Cheikhrouhou. A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment. Applied Soft Computing 2020, 93, 106385 -106385.

AMA Style

Amir Mohammad Fathollahi-Fard, Abbas Ahmadi, Fariba Goodarzian, Naoufel Cheikhrouhou. A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment. Applied Soft Computing. 2020; 93 ():106385-106385.

Chicago/Turabian Style

Amir Mohammad Fathollahi-Fard; Abbas Ahmadi; Fariba Goodarzian; Naoufel Cheikhrouhou. 2020. "A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment." Applied Soft Computing 93, no. : 106385-106385.

Methodologies and application
Published: 10 March 2020 in Soft Computing
Reads 0
Downloads 0

Nature has been considered as an inspiration of several recent meta-heuristic algorithms. This paper firstly studies and mimics the behavior of Scottish red deer in order to develop a new nature-inspired algorithm. The main inspiration of this meta-heuristic algorithm is to originate from an unusual mating behavior of Scottish red deer in a breading season. Similar to other population-based meta-heuristics, the red deer algorithm (RDA) starts with an initial population called red deers (RDs). They are divided into two types: hinds and male RDs. Besides, a harem is a group of female RDs. The general steps of this evolutionary algorithm are considered by the competition of male RDs to get the harem with more hinds via roaring and fighting behaviors. By solving 12 benchmark functions and important engineering as well as multi-objective optimization problems, the superiority of the proposed RDA shows in comparison with other well-known and recent meta-heuristics.

ACS Style

Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli; Reza Tavakkoli-Moghaddam. Red deer algorithm (RDA): a new nature-inspired meta-heuristic. Soft Computing 2020, 24, 14637 -14665.

AMA Style

Amir Mohammad Fathollahi-Fard, Mostafa Hajiaghaei-Keshteli, Reza Tavakkoli-Moghaddam. Red deer algorithm (RDA): a new nature-inspired meta-heuristic. Soft Computing. 2020; 24 (19):14637-14665.

Chicago/Turabian Style

Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli; Reza Tavakkoli-Moghaddam. 2020. "Red deer algorithm (RDA): a new nature-inspired meta-heuristic." Soft Computing 24, no. 19: 14637-14665.

Original paper
Published: 01 January 2020 in Clean Technologies and Environmental Policy
Reads 0
Downloads 0

The pollution and emission caused by the manufacturing, operation, and scrapping of marine ships have considerable impact on the environment. Therefore, it is essential to develop an effective and efficient approach toward evaluating the environmental impact of ships. This study uses the green degree of ships concept to evaluate different alternatives. Because environmental evaluation involves several criteria, the problem can be formulated as a traditional multi-criteria decision-making (MCDM) model. In this regard, the main innovation of this study is the development of an improved MCDM model using a novel hybrid method, namely the group fuzzy entropy and cloud technique for order of preference by similarity to ideal solution theory. The developed model calculates the criteria weight and rank based on the selected criteria and alternatives. Finally, a criteria system is developed to evaluate several classical alternatives, and various sensitivity analyses were carried out to validate the robustness of the proposed methodology. The results revealed that the model and criteria system can provide several quantitative and qualitative indicators for governmental policy-makers and agencies, environmental consultants, and environmental service organizations.

ACS Style

Xu Liu; Guangdong Tian; Amir Mohammad Fathollahi-Fard; Mohammad Mojtahedi. Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory. Clean Technologies and Environmental Policy 2020, 22, 493 -512.

AMA Style

Xu Liu, Guangdong Tian, Amir Mohammad Fathollahi-Fard, Mohammad Mojtahedi. Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory. Clean Technologies and Environmental Policy. 2020; 22 (2):493-512.

Chicago/Turabian Style

Xu Liu; Guangdong Tian; Amir Mohammad Fathollahi-Fard; Mohammad Mojtahedi. 2020. "Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory." Clean Technologies and Environmental Policy 22, no. 2: 493-512.

Journal article
Published: 01 December 2019 in International Journal of Engineering
Reads 0
Downloads 0
ACS Style

Nasrin Mehranfar; M. Hajiaghaei-Keshteli; Amir Mohammad Fathollahi-Fard. A Novel Hybrid Whale Optimization Algorithm to Solve a Production-Distribution Network Problem Considering Carbon Emissions. International Journal of Engineering 2019, 32, 1781 -1789.

AMA Style

Nasrin Mehranfar, M. Hajiaghaei-Keshteli, Amir Mohammad Fathollahi-Fard. A Novel Hybrid Whale Optimization Algorithm to Solve a Production-Distribution Network Problem Considering Carbon Emissions. International Journal of Engineering. 2019; 32 (12):1781-1789.

Chicago/Turabian Style

Nasrin Mehranfar; M. Hajiaghaei-Keshteli; Amir Mohammad Fathollahi-Fard. 2019. "A Novel Hybrid Whale Optimization Algorithm to Solve a Production-Distribution Network Problem Considering Carbon Emissions." International Journal of Engineering 32, no. 12: 1781-1789.

Journal article
Published: 31 October 2019 in Information Sciences
Reads 0
Downloads 0

The last century has seen an increased prevalence and duration of droughts as well as the water shortage especially in Middle East countries like Iran. This urgent situation in Iran such as Urmia Lake in the west Azerbaijan province is a motivation for us to model a new coordinated water supply and wastewater collection network design problem. Due to the uncertainty, as one of inherent sections of the water supply chain, a two-stage stochastic programming approach is used to formulate the problem. To solve the proposed model, a Lagrangian relaxation-based algorithm formulated by a new adaptive strategy is employed. This algorithm considers both upper and lower bounds of the problem to reach a performance solution. The proposed algorithm is compared with two similar algorithms from the literature to reveal its performance. As such, the efficiency of the proposed model is evaluated by some sensitivity analyses. Finally, a comprehensive discussion is provided to show the main findings and practical insights of this research.

ACS Style

Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli; Guangdong Tian; Zhiwu Li. An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem. Information Sciences 2019, 512, 1335 -1359.

AMA Style

Amir Mohammad Fathollahi-Fard, Mostafa Hajiaghaei-Keshteli, Guangdong Tian, Zhiwu Li. An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem. Information Sciences. 2019; 512 ():1335-1359.

Chicago/Turabian Style

Amir Mohammad Fathollahi-Fard; Mostafa Hajiaghaei-Keshteli; Guangdong Tian; Zhiwu Li. 2019. "An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem." Information Sciences 512, no. : 1335-1359.

Journal article
Published: 30 September 2019 in Computers & Industrial Engineering
Reads 0
Downloads 0

The truck scheduling problem is one of the most challenging and important types of scheduling with a large number of real-world applications in the area of logistics and cross-docking systems. This problem is formulated to find an optimal condition for both receiving and shipping trucks sequences. Due to the difficulty of the practicality of the truck scheduling problem for large-scale cases, the literature has shown that there is a chance, even with low possibility, for a new optimizer to outperform existing algorithms for this optimization problem. Already applied successfully to solve similar complicated optimization problems, the Social Engineering Optimizer (SEO) inspired by social engineering phenomena, has been never applied to the truck scheduling problem. This motivates us to develop a set of novel modifications of the recently-developed SEO. To validate these optimizers, they are evaluated by solving a set of standard benchmark functions. All the algorithms have been calibrated by the Taguchi experimental design approach to further enhance their optimization performance. In addition to some benchmarks of truck scheduling, a real case study to prove the proposed problem is utilized to show the high-efficiency of the developed optimizers in a real situation. The results indicate that the proposed modifications of SEO considerably outperform other existing algorithms in this research area and provide very competitive results.

ACS Style

Amir Mohammad Fathollahi-Fard; Mehdi Ranjbar-Bourani; Naoufel Cheikhrouhou; Mostafa Hajiaghaei-Keshteli. Novel modifications of social engineering optimizer to solve a truck scheduling problem in a cross-docking system. Computers & Industrial Engineering 2019, 137, 106103 .

AMA Style

Amir Mohammad Fathollahi-Fard, Mehdi Ranjbar-Bourani, Naoufel Cheikhrouhou, Mostafa Hajiaghaei-Keshteli. Novel modifications of social engineering optimizer to solve a truck scheduling problem in a cross-docking system. Computers & Industrial Engineering. 2019; 137 ():106103.

Chicago/Turabian Style

Amir Mohammad Fathollahi-Fard; Mehdi Ranjbar-Bourani; Naoufel Cheikhrouhou; Mostafa Hajiaghaei-Keshteli. 2019. "Novel modifications of social engineering optimizer to solve a truck scheduling problem in a cross-docking system." Computers & Industrial Engineering 137, no. : 106103.

Journal article
Published: 09 September 2019 in Applied Sciences
Reads 0
Downloads 0

Recently, there is of significant interest in developing multi-criteria decision making (MCDM) techniques with large applications for real-life problems. Making a reasonable and accurate decision on MCDM problems can help develop enterprises better. The existing MCDM methods, such as the grey comprehensive evaluation (GCE) method and the technique for order preference by similarity to an ideal solution (TOPSIS), have their one-sidedness and shortcomings. They neither consider the difference of shape and the distance of the evaluation sequence of alternatives simultaneously nor deal with the interaction that universally exists among criteria. Furthermore, some enterprises cannot consult the best professional expert, which leads to inappropriate decisions. These reasons motivate us to contribute a novel hybrid MCDM technique called the grey fuzzy TOPSIS (FGT). It applies fuzzy measures and fuzzy integral to express and integrate the interaction among criteria, respectively. Fuzzy numbers are employed to help the experts to make more reasonable and accurate evaluations. The GCE method and the TOPSIS are combined to improve their one-sidedness. A case study of supplier evaluation of a collaborative manufacturing enterprise verifies the effectiveness of the hybrid method. The evaluation result of different methods shows that the proposed approach overcomes the shortcomings of GCE and TOPSIS. The proposed hybrid decision-making model provides a more accurate and reliable method for evaluating the fuzzy system MCDM problems with interaction criteria.

ACS Style

Yixiong Feng; Zhifeng Zhang; Guangdong Tian; Amir Mohammad Fathollahi-Fard; Nannan Hao; Zhiwu Li; Wenjie Wang; Jianrong Tan. A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise. Applied Sciences 2019, 9, 3770 .

AMA Style

Yixiong Feng, Zhifeng Zhang, Guangdong Tian, Amir Mohammad Fathollahi-Fard, Nannan Hao, Zhiwu Li, Wenjie Wang, Jianrong Tan. A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise. Applied Sciences. 2019; 9 (18):3770.

Chicago/Turabian Style

Yixiong Feng; Zhifeng Zhang; Guangdong Tian; Amir Mohammad Fathollahi-Fard; Nannan Hao; Zhiwu Li; Wenjie Wang; Jianrong Tan. 2019. "A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise." Applied Sciences 9, no. 18: 3770.